Decomposition of Two-Component Multivariate Signals with Overlapped Domains of Support

Time-frequency signal analysis has been an active research area for several decades. It provides efficient tools for the analysis and processing of signals with time-varying spectral content. However, the analysis and characterization of non-stationary signals with several components having overlapped domains of supports has been a particularly challenging topic. In this paper, we discuss the applicability of the multivariate signal paradigm to solve the problem of multicomponent signal decomposition. In particular, the paper is focused on bivariate two-component signal case, aiming to present the decomposition approach as simply as possible, demystifying the basic theoretical concepts. In the presented numerical experiments, we explore the limits of the approach subject to the additive noise.